Trail cameras and surveillance cameras often send image data that may be interpreted as false positives for detection of certain objects. These false positives can be caused by the motion of inanimate objects like limbs or leaves. False positives can also be caused by the movement of animate objects that are not being studied or pursued. The conventional strategy is to provide an end user with all captured footage. This often causes problems because the conventional strategy requires the end user to scour through a plurality of potentially irrelevant frames.
Furthermore, to provide just one example of a technical problem that may be addressed by the present disclosure, it is becoming increasingly important to monitor cervid populations and track the spread chronic diseases, including, without limitation, Chronic Wasting Disease (CWD). CWD has been found in approximately 50% of the states within the United States, and attempts must be made to contain the spread and eradicate affected animals. This often causes problems because the conventional strategy does not address the recognition of affected populations early enough to prevent further spreading of the disease.
Finally, it is also becoming increasingly important to monitor the makeup of animal populations based on age, sex and species. Being able to monitor by such categories allows interested parties, such as the Department of Natural Resources in various states, to properly track and monitor the overall health of large populations of relevant species within the respective state.